pandas.Series.rename

Series.rename(index=None, **kwargs)

Alter Series index labels or name

Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error.

Alternatively, change Series.name with a scalar value.

See the user guide for more.

Parameters:

index : scalar, hashable sequence, dict-like or function, optional

dict-like or functions are transformations to apply to the index. Scalar or hashable sequence-like will alter the Series.name attribute.

copy : boolean, default True

Also copy underlying data

inplace : boolean, default False

Whether to return a new %(klass)s. If True then value of copy is ignored.

level : int or level name, default None

In case of a MultiIndex, only rename labels in the specified level.

Returns:

renamed : Series (new object)

See also

pandas.Series.rename_axis

Examples

>>> s = pd.Series([1, 2, 3])
>>> s
0    1
1    2
2    3
dtype: int64
>>> s.rename("my_name") # scalar, changes Series.name
0    1
1    2
2    3
Name: my_name, dtype: int64
>>> s.rename(lambda x: x ** 2)  # function, changes labels
0    1
1    2
4    3
dtype: int64
>>> s.rename({1: 3, 2: 5})  # mapping, changes labels
0    1
3    2
5    3
dtype: int64